Differential diagnosis of ground-glass opacity nodules: CT number analysis by three-dimensional computerized quantification

Analysis of pulmonary pure ground-glass nodule in enhanced dual energy CT imaging for predicting invasive adenocarcinoma: comparing with conventional thin-section CT imaging

Background

To investigate the value of dual energy computed tomography (DECT) parameters (including iodine concentration and monochromatic CT numbers) for predicting pure ground-glass nodules (pGGNs) of invasive adenocarcinoma (IA).

Methods

A total of 55 resected pGGNs evaluated with both unenhanced thin-section CT (TSCT) and enhanced DECT scans were included. Correlations between histopathology [adenocarcinoma in situ (AIS), minimally IA (MIA), and IA] and CT scan characteristics were examined. CT scan and clinicodemographic data were investigated by univariate and multivariate analysis to identify features that helped distinguish IA from AIS or MIA.

Results

Both normalized iodine concentration (NIC) of IA and slope of spectral curve [slope(k)] were not significantly different between IA and AIS or MIA. Size, performance of pleural retraction and enhanced monochromatic CT attenuation values of 120-140 keV were significantly higher for IA. In multivariate regression analysis, size and enhanced monochromatic CT number of 140 keV were independent predictors for IA. Using the two parameters together, the diagnostic capacity of IA could be improved from 0.697 or 0.635 to 0.713.

Conclusions

DECT could help demonstrate blood supply and indicate invasion extent of pGGNs, and monochromatic CT number of higher energy (especially 140 keV) would be better for diagnosing IA than lower energies. Together with size of pGGNs, the diagnostic capacity of IA could be better.

Semiquantative Visual Assessment of Sub-solid Pulmonary Nodules ≦3 cm in Differentiation of Lung Adenocarcinoma Spectrum

We aimed to analyze CT features of persistent subsolid nodules (SSN) ≦3 cm diagnosed pathologically as adenocarcinoma spectrum to investigate whether parameters enable distinction between invasive pulmonary adenocarcinomas (IPAs) and pre-invasive lesions. A total of 129 patients with 141 SSNs confirmed with surgically pathologic proof were retrospectively reviewed. Of 141 SSNs, there were 57 pure ground-glass nodules (GGNs), 22 heterogeneous GGNs, and 62 part-solid nodules. SSN subclassification showed a significant linear trend with invasive degree of the adenocarcinoma spectrum (pure GGNs 7%; heterogeneous GGNs 36.4%; part-solid nodules 85.5%, P for trend <0.0001). For IPA detection in 141 SSNs, a solid part of ≧3 mm was the most specificity (sensitivity, 76.9%; specificity, 94.7%), followed by air-bronchogram sign (sensitivity, 53.8%; specificity, 89.5%), SSN subclassification (sensitivity, 81.5%; specificity, 88.2%), and a lesion size ≧12 mm (sensitivity, 84.6%; specificity, 76.3%). For IPA detection in 79 pure or heterogeneous GGNs, the heterogeneous GGN sign was the most useful finding, with most specificity (sensitivity, 66.7%; specificity, 79.1%), followed by CT attenuation (HU) of ≧-493 (sensitivity, 75%; specificity, 74.6%) and a lesion size ≧10 mm (sensitivity, 83.3%; specificity, 70.1%). In conclusion, this simple combined visual and semiquantitative analysis of CT features helps distinguish IPAs from pre-invasive lesions.

Computer-Aided Diagnosis of Ground-Glass Opacity Nodules Using Open-Source Software for Quantifying Tumor Heterogeneity

OBJECTIVE

The purposes of this study are to develop quantitative imaging biomarkers obtained from high-resolution CTs for classifying ground-glass nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC); to evaluate the utility of contrast enhancement for differential diagnosis; and to develop and validate a support vector machine (SVM) to predict the GGN type.

MATERIALS AND METHODS

The heterogeneity of 248 GGNs was quantified using custom software. Statistical analysis with a univariate Kruskal-Wallis test was performed to evaluate metrics for significant differences among the four GGN groups. The heterogeneity metrics were used to train a SVM to learn and predict the lesion type.

RESULTS

Fifty of 57 and 51 of 57 heterogeneity metrics showed statistically significant differences among the four GGN groups on unenhanced and contrast-enhanced CT scans, respectively. The SVM predicted lesion type with greater accuracy than did three expert radiologists. The accuracy of classifying the GGNs into the four groups on the basis of the SVM algorithm was 70.9%, whereas the accuracy of the radiologists was 39.6%. The accuracy of SVM in classifying the AIS and MIA nodules was 73.1%, and the accuracy of the radiologists was 35.7%. For indolent versus invasive lesions, the accuracy of the SVM was 88.1%, and the accuracy of the radiologists was 60.8%. We found that contrast enhancement does not significantly improve the differential diagnosis of GGNs.

CONCLUSION

Compared with the GGN classification done by the three radiologists, the SVM trained regarding all the heterogeneity metrics showed significantly higher accuracy in classifying the lesions into the four groups, differentiating between AIS and MIA and between indolent and invasive lesions. Contrast enhancement did not improve the differential diagnosis of GGNs.

Can we differentiate minimally invasive adenocarcinoma and non-invasive neoplasms based on high-resolution computed tomography features of pure ground glass nodules?

Objective

The purpose of our study was to assess the differentially diagnostic value of radiographic characteristics of pure ground glass nodules (GGNs) between minimally invasive adenocarcinoma and non-invasive neoplasm.

Methods

Sixty-seven pure GGNs (28 minimally invasive adenocarcinomas (MIA) and 39 pre-invasive lesions) were analyzed from June 2012 to June 2015. Pre-invasive lesions consisted of 15 atypical adenomatous hyperplasia (AAH) and 24 adenocarcinomas in situ (AIS). High-resolution computed tomography (HRCT) features and volume of MIA and pre-invasive lesions were assessed. Fisher exact test, independent sample t test, Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were performed.

Results

Inter-observer agreement indexes for the diameter, mean HRCT attenuations and volume of pure GGNs were all high (ICC>0.75). Univariate analyses showed that lesion diameter, mean HRCT attenuation, and volume value differed significantly between two groups. Among HRCT findings, GGN shape as round or oval (F = 13.456, P = 0.002) and lesion borders as smooth or notched (F = 15.742, P = 0.001) frequently appeared in pre-invasive lesions in comparison with MIA. Type II and type III of the relationship between blood vessels and pure GGNs suggested higher possibility of malignancy than type I.

Conclusions

HRCT features of pure GGNs can help to differentiate MIA from non-invasive neoplasms.

Three-dimensional substructure measurements for the differential diagnosis of ground glass nodules

BACKGROUND

We analyzed the differences between maximum and peak computed tomography (CT) numbers (M-P), respectively representing the densities of the solid center and the main periphery of ground-glass nodules (GGNs), and the average change in M-P velocity (V(M-P)) during follow-up to differentiate between pre-invasive (PIA) and invasive adenocarcinoma (IAC).

METHODS

Data of 102 patients were retrospectively collected and analyzed in our study including 43 PIAs and 59 IACs. Diameters, total volumes, and the maximum and peak CT numbers in CT number histograms were measured and followed for at least 3 months. This study was registered retrospectively.

RESULTS

The M-P values for IACs were higher than those for PIAs (p = 0.001), with an area under the curve (AUC) of 0.810 and a threshold of 489.5 Hounsfield units (HU) in ROC analysis. The V(M-P) values for IACs were smaller than those for PIAs (p = 0.04), with an AUC of 0.805 and a threshold of 11.01 HU/day.

CONCLUSIONS

M-P and V(M-P) values may help distinguish IACs from PIAs by representing the changes in the sub-structural densities of GGNs during follow-up.

Tumor invasiveness defined by IASLC/ATS/ERS classification of ground-glass nodules can be predicted by quantitative CT parameters

BACKGROUND

To investigate the potential value of CT parameters to differentiate ground-glass nodules between noninvasive adenocarcinoma and invasive pulmonary adenocarcinoma (IPA) as defined by IASLC/ATS/ERS classification.

METHODS

We retrospectively reviewed 211 patients with pathologically proved stage 0-IA lung adenocarcinoma which appeared as subsolid nodules, from January 2012 to January 2013 including 137 pure ground glass nodules (pGGNs) and 74 part-solid nodules (PSNs). Pathological data was classified under the 2011 IASLC/ATS/ERS classification. Both quantitative and qualitative CT parameters were used to determine the tumor invasiveness between noninvasive adenocarcinomas and IPAs.

RESULTS

There were 154 noninvasive adenocarcinomas and 57 IPAs. In pGGNs, CT size and area, one-dimensional mean CT value and bubble lucency were significantly different between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate regression and ROC analysis revealed that CT size and one-dimensional mean CT value were predictive of noninvasive adenocarcinomas compared to IPAs. Optimal cutoff value was 13.60 mm (sensitivity, 75.0%; specificity, 99.6%), and -583.60 HU (sensitivity, 68.8%; specificity, 66.9%). In PSNs, there were significant differences in CT size and area, solid component area, solid proportion, one-dimensional mean and maximum CT value, three-dimensional (3D) mean CT value between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate and ROC analysis showed that CT size and 3D mean CT value were significantly differentiators. Optimal cutoff value was 19.64 mm (sensitivity, 53.7%; specificity, 93.9%), -571.63 HU (sensitivity, 85.4%; specificity, 75.8%).

CONCLUSIONS

For pGGNs, CT size and one-dimensional mean CT value are determinants for tumor invasiveness. For PSNs, tumor invasiveness can be predicted by CT size and 3D mean CT value.

Mean Computed Tomography Value to Predict the Tumor Invasiveness in Clinical Stage IA Lung Cancer

BACKGROUND

The purpose of this study was to validate the ability of the mean computed tomography (m-CT) value to predict tumor invasiveness and recurrence, and further, to compare with other measurements such as consolidation/tumor ratio and solid tumor size.

METHODS

A retrospective study was conducted of 494 patients with clinical stage IA lung cancer who had peripherally located lung adenocarcinoma. Receiver operating characteristic curve analysis was used to compare the ability to predict tumor invasiveness and recurrence between m-CT value, consolidation/tumor ratio, and tumor size. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of pathologic, less invasive lung cancer. Disease-free survival was measured from the date of the operation until any recurrence.

RESULTS

The m-CT values were 643.6 ± 9.4 Hounsfield units in the noninvasive cancer group and 365.9 ± 11.4 Hounsfield units in the invasive cancer group (p < 0.0001). The invasive cancer group was strongly associated with a high CT attenuation value, high consolidation/tumor ratio, large solid tumor size, large tumor size, and high standardized uptake value. Multiple logistic analyses, including the preoperatively determined variables, revealed that standardized uptake value and m-CT are independent predictive factors of less invasive lung cancer. In addition, the hazard ratio of the m-CT value was higher than that of the standardized uptake value value.

CONCLUSIONS

The evaluation of m-CT value is useful in predicting less invasive lung cancer. The m-CT value can potentially determine operative procedure, particularly limited resection for peripheral lung adenocarcinoma.

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography

PURPOSE

To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans.

METHODS AND MATERIALS

Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed.

RESULTS

During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R² > 0.99) and correlates weakly with the change in GTV (R² = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction.

CONCLUSION

Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.

Pulmonary ground-glass opacity: computed tomography features, histopathology and molecular pathology

The incidence of pulmonary ground-glass opacity (GGO) lesions is increasing as a result of the widespread use of multislice spiral computed tomography (CT) and the low-dose CT screening for lung cancer detection. Besides benign lesions, GGOs can be a specific type of lung adenocarcinomas or their preinvasive lesions. Evaluation of pulmonary GGO and investigation of the correlation between CT imaging features and lung adenocarcinoma subtypes or driver genes can be helpful in confirming the diagnosis and in guiding the clinical management. Our review focuses on the pathologic characteristics of GGO detected at CT, involving histopathology and molecular pathology.

Evaluation of Semi-automatic Segmentation Methods for Persistent Ground Glass Nodules on Thin-Section CT Scans

Objectives

This work was a comparative study that aimed to find a proper method for accurately segmenting persistent ground glass nodules (GGN) in thin-section computed tomography (CT) images after detecting them.

Methods

To do this, we first applied five types of semi-automatic segmentation methods (i.e., level-set-based active contour model, localized region-based active contour model, seeded region growing, K-means clustering, and fuzzy C-means clustering) to preprocessed GGN images, respectively. Then, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by two radiologists.

Results

Comparison experiments were performed using 40 persistent GGNs. In our experiment, the mean Dice coefficient for each semiautomatic segmentation tool with manually segmented area was 0.808 for the level-set-based active contour model, 0.8001 for the localized region-based active contour model, 0.629 for seeded region growing, 0.7953 for K-means clustering, and 0.7999 for fuzzy C-means clustering, respectively.

Conclusions

The level-set-based active contour model algorithm showed the best performance, which was most similar to the result of manual segmentation by two radiologists. From the differentiation between the normal parenchyma and the nodule, it was also the most efficient. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for more accurate early diagnosis and prognosis of lung cancer in thin-section CT images.

Lung adenocarcinomas: correlation of computed tomography and pathology findings

Adenocarcinoma is the most common histologic type of lung cancer. Recent lung adenocarcinoma classifications from the International Association for the Study of Lung cancer, the American Thoracic Society and the European Respiratory Society (IASLC/ETS/ERS, 2011) and World Health Organization (WHO, 2015) define a wide range of adenocarcinoma types and subtypes featuring different prognosis and management. This spectrum of lesions translates into various CT presentations and features, which generally show good correlation with histopathology, stressing the key role of the radiologist in the diagnosis and management of those patients. This review aims at helping radiologists to understand the basics of the up-to-date adenocarcinoma pathological classifications, radio-pathological correlations and how to use them in the clinical setting, as well as other imaging-related correlations (radiogenomics, quantitative analysis, PET-CT).

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.

Thin-section computed tomography-histopathologic comparisons of pulmonary focal interstitial fibrosis, atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma with pure ground-glass opacity

OBJECTIVE

To retrospectively compare focal interstitial fibrosis (FIF), atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and minimally invasive adenocarcinoma (MIA) with pure ground-glass opacity (GGO) using thin-section computed tomography (CT).

MATERIALS AND METHODS

Sixty pathologically confirmed cases were reviewed including 7 cases of FIF, 17 of AAH, 23of AIS, and 13 of MIA. All nodules kept pure ground glass appearances before surgical resection and their last time of thin-section CT imaging data before operation were collected. Differences of patient demographics and CT features were compared among these four types of lesions.

RESULTS

FIF occurred more frequently in males and smokers while the others occurred more frequently in female nonsmokers. Nodule size was significant larger in MIA (P<0.001, cut-off value=7.5mm). Nodule shape (P=0.045), margin characteristics (P<0.001), the presence of pleural indentation (P=0.032), and vascular ingress (P<0.001) were significant factors that differentiated the 4 groups. A concave margin was only demonstrated in a high proportion of FIF at 85.7% (P=0.002). There were no significant differences (all P>0.05) in age, malignant history, attenuation value, location, and presence of bubble-like lucency.

CONCLUSION

A nodule size >7.5mm increases the possibility of MIA. A concave margin could be useful for differentiation of FIF from the other malignant or pre-malignant GGO nodules. The presence of spiculation or pleural indentation may preclude the diagnosis of AAH.

AKAP4 is a circulating biomarker for non-small cell lung cancer

Cancer testis antigens (CTAs) are widely expressed in tumor tissues, circulating tumor cells (CTCs) and in cancer derived exosomes that are frequently engulfed by lymphoid cells. To determine whether tumor derived CTA mRNAs could be detected in RNA from purified peripheral blood mononuclear cells (PBMC) of non-small cell lung cancer (NSCLC) patients, we assayed for the expression of 116 CTAs in PBMC RNA in a discovery set and identified AKAP4 as a potential NSCLC biomarker. We validated AKAP4 as a highly accurate biomarker in a cohort of 264 NSCLCs and 135 controls from 2 different sites including a subset of controls with high risk lung nodules. When all (264) lung cancers were compared with all (135) controls the area under the ROC curve (AUC) was 0.9714. When 136 stage I NSCLC lung cancers are compared with all controls the AUC is 0.9795 and when all lung cancer patients were compared to 27 controls with histologically confirmed benign lung nodules, a comparison of significant clinical importance, the AUC was 0.9825. AKAP4 expression increases significantly with tumor stage, but independent of age, gender, smoking history or cancer subtype. Follow-up studies in a small number of resected NSCLC patients revealed a decrease of AKAP4 expression post-surgical resection that remained low in patients in remission and increased with tumor recurrence. AKAP4 is a highly accurate biomarker for the detection of early stage lung cancer.

The IASLC Lung Cancer Staging Project: Background Data and Proposals for the Application of TNM Staging Rules to Lung Cancer Presenting as Multiple Nodules with Ground Glass or Lepidic Features or a Pneumonic Type of Involvement in the Forthcoming Eighth Edition of the TNM Classification

INTRODUCTION

Application of tumor, node, and metastasis (TNM) classification is difficult in patients with lung cancer presenting as multiple ground glass nodules or with diffuse pneumonic-type involvement. Clarification of how to do this is needed for the forthcoming eighth edition of TNM classification.

METHODS

A subcommittee of the International Association for the Study of Lung Cancer Staging and Prognostic Factors Committee conducted a systematic literature review to build an evidence base regarding such tumors. An iterative process that included an extended workgroup was used to develop proposals for TNM classification.

RESULTS

Patients with multiple tumors with a prominent ground glass component on imaging or lepidic component on microscopy are being seen with increasing frequency. These tumors are associated with good survival after resection and a decreased propensity for nodal and extrathoracic metastases. Diffuse pneumonic-type involvement in the lung is associated with a worse prognosis, but also with a decreased propensity for nodal and distant metastases.

CONCLUSION

For multifocal ground glass/lepidic tumors, we propose that the T category be determined by the highest T lesion, with either the number of tumors or m in parentheses to denote the multifocal nature, and that a single N and M category be used for all the lesions collectively-for example, T1a(3)N0M0 or T1b(m)N0M0. For diffuse pneumonic-type lung cancer we propose that the T category be designated by size (or T3) if in one lobe, as T4 if involving an ipsilateral different lobe, or as M1a if contralateral and that a single N and M category be used for all pulmonary areas of involvement.

Quantitative CT Scanning Analysis of Pure Ground-Glass Opacity Nodules Predicts Further CT Scanning Change

BACKGROUND

We sought to determine whether quantitative analysis of lung adenocarcinoma manifesting as a ground-glass opacity (GGO) nodule (GGN) on initial CT scans can predict further CT scanning change or rate of growth.

METHODS

This retrospective study included patients with lung adenocarcinoma manifesting as pure GGN on initial CT scans who were followed up with interval CT scanning until resection. All pure GGNs were classified based on CT scanning interval change in three subgroups as follows: group A (development of solid component), group B (growth of GGO component), and group C (no change in size). Nodule size, volume, density, mass, and CT scanning attenuation values were assessed from initial CT data sets.

RESULTS

Fifty-four pure GGNs were enrolled and classified into group A (n = 9), group B (n = 25), and group C (n = 20). Nodule size, volume, mass, and density of the GGNs in each subgroup were not significantly different. The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile were significantly different among the three subgroups (P = .02, P < .00). Three of nine (33%) pure GGNs showing a new solid component developed a solid component within 6 months.

CONCLUSIONS

The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile could be helpful in predicting future CT scanning change and growth rate of pure GGNs. Pure GGNs showing higher 97.5th percentile CT scanning attenuation values and steeper slopes of CT scanning attenuation values may require more frequent follow-up than the usual interval of 6 months.

Pulmonary ground-glass nodules diagnosis: mean change rate of peak CT number as a discriminative factor of pathology during a follow-up

OBJECTIVE

We aimed to analyse the peak CT number (PEAK) in CT number histogram of ground-glass nodules (GGN), meaning the most frequent density of pixels in the image of pulmonary nodule, based on three-dimensional (3D) reconstructive model pre-operatively, and the mean rate of PEAK change (V-PEAK) during a follow-up of GGN for differential diagnosis between pre-invasive adenocarcinoma (PIA) and invasive adenocarcinoma (IAC).

METHODS

CT number histogram of pixels in GGN was made automatically by 3D measurement software. Diameter, total volume, PEAK and V-PEAK were measured from CT data sets of different groups classified by pathology, subtype and number of GGN, respectively.

RESULTS

Among all 102 cases, 47 were PIA, including atypical adenomatous hyperplasia (n = 29) and adenocarcinoma in situ (n = 18), and 55 were IAC, including minimally IAC (MIA, n = 4). By Wilcoxon test, PEAK of IAC was significantly higher than that of PIA (p < 0.001). By receiver operating curve analysis, area under the curve (AUC) was 0.857 and threshold -820.50 Hounsfield units (HU) for differentiation between PIA and IAC. V-PEAK of IAC was unexpectedly remarkably smaller than that of PIA (p < 0.001) with AUC and threshold being 0.810 and -0.829 HU day(-1), respectively.

CONCLUSION

Pre-operative PEAK and V-PEAK, which interpret and evaluate the change of volume and density of pulmonary nodule simultaneously from both exterior and interior perspectives, can help to distinguish IAC from PIA.

ADVANCES IN KNOWLEDGE

This study provided researchers of GGN another perspective, taking both volume and density of nodules into consideration for pathological evaluation.

Quantitative diagnosis of connective tissue disease-associated interstitial pneumonia using thoracic computed tomography images

Patients with polymyositis (PM) or dermatomyositis (DM) frequently show interstitial pneumonia (IP), which is sometimes rapidly progressive or resistant to treatment, thereby significantly affecting the prognosis. The diagnosis and response evaluation of IP are commonly performed qualitatively based on imaging findings, which may cause disagreement among rheumatologists in the evaluation of early lesions and atypical interstitial changes. To determine whether IP could be diagnosed in a quantitative manner during the early stage of PM/DM using a workstation that allows quantitative image processing. Thoracic computed tomography (CT) images of 20 PM/DM patients were reconstructed into a three-dimensional (3D) image using an image processing workstation. The CT values of the constituent voxels were arranged in a histogram of -1000 to +1000 Hounsfield units (HU). The most frequent lung field density was -900 to -801 HU, and relative size was as follows: IP (+) group 0.45 and IP (-) group 0.53. Between -1000 and -701 HU, relative size was not significantly different between the IP (+) group and IP (-) group. Between -700 and -1 HU, the relative size of the lung field was significantly larger in the IP (+) than in the IP (-) group, demonstrating its IP-diagnosing ability. Particularly, within the range from -700 to -301 HU, the macroscopically-assessed ground glass opacity was consistent with the CT value, which, in turn, was closely correlated with KL-6, the pre-existing marker for IP diagnosis. The results of this study may lead to the establishment of quantitative methods of evaluating IP and possible elucidation of the pathogenesis of IP.

Surgical treatment of early-stage non-small-cell lung cancer

Surgical resection remains the standard of care for functionally operable early-stage non-small-cell lung cancer (NSCLC) and resectable stage IIIA disease. The role of invasive staging and restaging techniques is currently being debated, but they provide the largest biopsy samples which allow for precise mediastinal staging. Different types of operative procedures are currently available to the thoracic surgeon, and some of these interventions can be performed by video-assisted thoracic surgery (VATS) with the same oncological results as those by open thoracotomy. The principal aim of surgical treatment for NSCLC is to obtain a complete resection which has been precisely defined by a working group of the International Association for the Study of Lung Cancer (IASLC). Intraoperative staging of lung cancer is of utmost importance to decide on the extent of resection according to the intraoperative tumour (T) and nodal (N) status. Systematic nodal dissection is generally advocated to evaluate the hilar and mediastinal lymph nodes which are subdivided into seven zones according to the most recent 7th tumour-node-metastasis (TNM) classification. Lymph-node involvement not only determines prognosis but also the administration of adjuvant therapy.

In 2011, a new multidisciplinary adenocarcinoma classification was published introducing the concepts of adenocarcinoma in situ and minimally invasive adenocarcinoma. This classification has profound surgical implications. The role of limited or sublobar resection, comprising anatomical segmentectomy and wide wedge resection, is reconsidered for early-stage lesions which are more frequently encountered with the recently introduced large screening programmes. Numerous retrospective non-randomised studies suggest that sublobar resection may be an acceptable surgical treatment for early lung cancers, also when performed by VATS.

More tailored, personalised therapy has recently been introduced. Quality-of-life parameters and surgical quality indicators become increasingly important to determine the short-term and long-term impact of a surgical procedure. International databases currently collect extensive surgical data, allowing more precise calculation of mortality and morbidity according to predefined risk factors. Centralisation of care has been shown to improve results. Evidence-based guidelines should be further developed to provide optimal staging and therapeutic algorithms.

Correlation between histological invasiveness and the computed tomography value in pure ground-glass nodules

Purpose

The purpose of this study was to evaluate the correlation between histological invasiveness and the computed tomography (CT) value and size in pure ground-glass nodules (GGNs) to determine optimal “follow-up or resection” strategies.

Methods

Between 2001 and 2014, 78 resected, pure GGNs were retrospectively evaluated. The maximum diameter and CT value of pure GGNs were measured using a computer graphics support system.

Results

All GGNs with a maximum diameter ≤10 mm and CT value ≤−600 Hounsfield units (HU) were considered to be noninvasive lesions, while 21 of 26 (81 %) with a maximum diameter >10 mm and CT value >−600 HU were considered to be invasive lesions. With respect to the correlation between each histological type and pure GGN with a maximum diameter ≤10 mm and CT value ≤−600 HU, the specificity was 90 % and the sensitivity and negative predictive value were both 100 % in atypical adenomatous hyperplasia (AAH), while the specificity was 58 % and the sensitivity and positive predictive value were 0 % in minimally invasive and invasive adenocarcinoma.

Conclusion

Pure GGNs with a maximum diameter of ≤10 mm and CT value of ≤−600 HU are nearly always pre-invasive lesions; therefore, surgery should be carefully selected in such patients.

Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)

The aim of this study was to predict Ki-67 labeling index (LI) preoperatively by three-dimensional (3D) CT image parameters for pathologic assessment of GGO nodules. Diameter, total volume (TV), the maximum CT number (MAX), average CT number (AVG) and standard deviation of CT number within the whole GGO nodule (STD) were measured by 3D CT workstation. By detection of immunohistochemistry and Image Software Pro Plus 6.0, different Ki-67 LI were measured and statistically analyzed among preinvasive adenocarcinoma (PIA), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC). Receiver operating characteristic (ROC) curve, Spearman correlation analysis and multiple linear regression analysis with cross-validation were performed to further research a quantitative correlation between Ki-67 labeling index and radiological parameters. Diameter, TV, MAX, AVG and STD increased along with PIA, MIA and IAC significantly and consecutively. In the multiple linear regression model by a stepwise way, we obtained an equation: prediction of Ki-67 LI=0.022*STD+0.001* TV+2.137 (R=0.595, R’s square=0.354, p<0.001), which can predict Ki-67 LI as a proliferative marker preoperatively. Diameter, TV, MAX, AVG and STD could discriminate pathologic categories of GGO nodules significantly. Ki-67 LI of early lung adenocarcinoma presenting GGO can be predicted by radiologic parameters based on 3D CT for differential diagnosis.

Quantitative CT analysis of pulmonary ground-glass opacity nodules for distinguishing invasive adenocarcinoma from non-invasive or minimally invasive adenocarcinoma: the added value of using iodine mapping

OBJECTIVES

To determine whether quantitative analysis of iodine-enhanced images generated from dual-energy CT (DECT) have added value in distinguishing invasive adenocarcinoma from non-invasive or minimally invasive adenocarcinoma (MIA) showing ground-glass nodule (GGN).

METHODS

Thirty-four patients with 39 GGNs were enrolled in this prospective study and underwent DECT followed by complete tumour resection. Various quantitative imaging parameters were assessed, including virtual non-contrast (VNC) imaging and iodine-enhanced imaging.

RESULTS

Of all 39 GGNs, four were adenocarcinoma in situ (AIS) (10 %), nine were MIA (23 %), and 26 were invasive adenocarcinoma (67 %). When assessing only VNC imaging, multivariate analysis revealed that mass, uniformity, and size-zone variability were independent predictors of invasive adenocarcinoma (odds ratio [OR] = 19.92, P = 0.02; OR = 0.70, P = 0.01; OR = 16.16, P = 0.04, respectively). After assessing iodine-enhanced imaging with VNC imaging, both mass on the VNC imaging and uniformity on the iodine-enhanced imaging were independent predictors of invasive adenocarcinoma (OR = 5.51, P = 0.04 and OR = 0.67, P < 0.01). The power of diagnosing invasive adenocarcinoma was improved after adding the iodine-enhanced imaging parameters versus VNC imaging alone, from 0.888 to 0.959, respectively (P = 0.029).

CONCLUSION

Quantitative analysis using iodine-enhanced imaging metrics versus VNC imaging metrics alone generated from DECT have added value in distinguishing invasive adenocarcinoma from AIS or MIA.

KEY POINTS

Quantitative analysis using DECT was used to distinguish invasive adenocarcinoma. Tumour mass and uniformity were independent predictors of invasive adenocarcinoma. Diagnostic performance was improved after adding iodine parameters to VNC parameters.

Diagnosis of the invasiveness of lung adenocarcinoma manifesting as ground glass opacities on high-resolution computed tomography

BACKGROUND

To explore the diagnostic method in assessing the malignancy of pulmonary adenocarcinoma characterized by ground glass opacities (GGO) on computed tomography (CT).

METHODS

Preoperative CT data for preinvasive and invasive lung adenocarcinomas were analyzed retrospectively. GGO lesions that were detected on lung windows but absent using the mediastinal window were subject to adjustment of the window width, which was reduced with the fixed interval of 100 HU until the lesions were no longer evident, with a fixed mediastinal window level of 40 HU. The shape, smoking habits, size of the lesion on the lung window, and window width at which lesions disappeared were compared and receiver operating characteristic curves were used to determine the optimal cut-off of the lesion size and window width to differentiate between these invasive and preinvasive lesions.

RESULTS

Of the 209 lung adenocarcinomas, 102 were preinvasive (25 atypical adenomatous hyperplasia and 77 adenocarcinoma in situ), while 107 were invasive (78 minimally invasive adenocarcinoma and 29 invasive adenocarcinoma). The shape, lesion size, and window width at which lesions were no longer evident differed significantly between the two groups (P < 0.05). The size of 8.9 mm and a window width of 1250 HU were the optimal cut-off to differentiate between preinvasive and invasive lesions.

CONCLUSION

The shape, size of the lesion, and window width on high-resolution CT may be useful in assessing the invasiveness of lung adenocarcinoma that manifests as GGO. Irregular lesions that disappear at window width <1250 HU, with a diameter of > 8.9 mm are more likely to be invasive.

CT characteristics and pathological implications of early stage (T1N0M0) lung adenocarcinoma with pure ground-glass opacity

OBJECTIVES

To analyze the CT characteristics and pathological classification of early lung adenocarcinoma (T1N0M0) with pure ground-glass opacity (pGGO).

METHODS

Ninety-four lesions with pGGO on CT in 88 patients with T1N0M0 lung adenocarcinoma were selected from January 2010 to December 2012. All lesions were confirmed by pathology. CT appearances were analyzed including lesion location, size, density, uniformity, shape, margin, tumour-lung interface, internal and surrounding malignant signs. Lesion size and density were compared using analysis of variance, lesion size also assessed using ROC curves. Gender of patients, lesion location and CT appearances were compared using χ²-test.

RESULTS

There were no significant differences in gender, lesion location and density with histological invasiveness (P > 0.05). The ROC curve showed that the possibility of invasive lesion was 88.73% when diameter of lesion was more than 10.5 mm. There was a significant difference between lesion uniformity and histological invasiveness (P = 0.01). There were significant differences in margin, tumour-lung interface, air bronchogram with histological invasiveness ( P = 0.02,P = 0.00,P = 0.048). The correlation index of lesion size and uniformity was r = 0.45 (P = 0.00).

CONCLUSIONS

The lesion size and uniformity, tumour-lung interface and the air bronchogram can help predict invasive extent of early stage lung adenocarcinoma with pGGO.

KEY POINTS

• CT characteristics and pathological classification of pGGO lung adenocarcinoma smaller than 3 cm • The optimal cut-off value for discriminating preinvasive from invasive lesions was 10.5 mm • Uniformity was significant difference between histological subtypes and correlated with lesion size • Tumour margin, tumour-lung interface and air bronchogram showed different between histological types • No significant difference in gender, lesion location and density with histological subtypes.

Morphological factors differentiating between early lung adenocarcinomas appearing as pure ground-glass nodules measuring ≤10 mm on thin-section computed tomography

Background

We aimed to compare the morphological features of pure ground-glass nodules (GGNs; diameter, ≤10 mm) on thin-section computed tomography (TSCT) with their histopathological results in order to identify TSCT features differentiating between atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA).

Methods

Between January and December 2013, 205 pure GGNs with a diameter ≤10 mm on TSCT were pathologically confirmed as AAH (40), AIS (95) or MIA (70) lesions. The patients’ age and sex were recorded. The morphological features were evaluated, and maximum diameter and mean CT value were measured for each nodule. F test, Pearson χ² test, Fisher exact test and multinomial logistic regression analysis were used to identify factors differentiating between AAH, AIS and MIA. Receiver operating characteristic (ROC) curve analysis was performed for maximum diameter and mean CT value.

Results

F test, Pearson χ² test and Fisher exact test revealed that maximum diameter (P <0.00001), mean CT value (P =0.005), type of interface (P =0.005) and presence of air bronchograms (P =0.02, n =44) significantly differed among the AAH, AIS and MIA groups. Multinomial logistic regression analysis showed that maximum diameter ≥6.5 mm, a well-defined and coarse interface indicated AIS or MIA rather than AAH; air bronchograms differentiated MIA from AAH; but these parameters did not differentiate between AIS and MIA. A mean CT value less than −520 HU indicated AAH or AIS rather than MIA, but did not differentiate between AAH and AIS.

Conclusions

In the case of pure GGNs measuring ≤10 mm, a maximum diameter ≥6.5 mm, a well-defined and coarse interface indicate AIS or MIA rather than AAH; an air bronchogram can differentiate MIA from AAH. A mean CT value less than −520 HU indicates AAH or AIS rather than MIA.

The revised lung adenocarcinoma classification-an imaging guide

Advances in our understanding of the pathology, radiology and clinical behaviour of peripheral lung adenocarcinomas facilitated a more robust terminology and classification of these lesions. The International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) classification introduced new terminology to better reflect this heterogeneous group of adenocarcinomas formerly known as bronchoalveolar cell carcinoma (BAC). There is now a clear distinction between pre-invasive, minimally invasive and frankly invasive lesions. The radiographic appearance of these ranges from pure ground glass nodules to solid mass lesions. Radiologists must be aware of the new classification in order to work alongside multidisciplinary colleagues to allow accurate staging and treatment. This article reviews the new classification of lung adenocarcinomas. Management options of these lesions with particular focus on radiological implications of the new classification will be reviewed.

The lung adenocarcinoma guidelines: what to be considered by surgeons

In 2011 the International Association for the Study of Lung Cancer (IASLC), the American Thoracic Society (ATS), and the European Respiratory Society (ERS), have proposed a new subclassification of lung adenocarcinomas. This new classification was founded on an evidence-based approach to a systematic review of 11,368 citations from the related literature. Validation has involved projects relating to histologic and cytologic analysis of small biopsy specimens, histologic subtyping, grading, and observer variation among expert pathologists. As enormous resources are being spent on trials involving molecular and therapeutic aspects of adenocarcinoma of the lung, the development of standardized criteria is of great importance and should help advance the field, increasing the impact of research, and improving patient care. This classification is needed to assist in determining patient therapy and predicting outcome. The 2011 IASLC/ATS/ERS adenocarcinoma classification can have an impact on TNM staging. It may help in comparing histologic characteristics of multiple lung adenocarcinomas to determine whether they are intrapulmonary metastases versus separate primaries. Use of comprehensive histologic subtyping along with other histologic characteristics has been shown to have good correlation with molecular analyses and clinical behavior. Also, it may be more meaningful clinically to measure tumor size in lung adenocarcinomas that have a lepidic component by using invasive size rather than total size to determine the size T factor.

Quantitative CT analysis of pulmonary ground-glass opacity nodules for the distinction of invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma

Objectives

We aimed to analyze the CT findings of ground-glass opacity nodules diagnosed pathologically as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma in order to investigate whether quantitative CT parameters enable distinction of invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma.

Methods

We reviewed CT images and pathologic specimens from 191 resected ground-glass opacity nodules with little or no solid component at CT. Nodule size, volume, density, mass, skewness/kurtosis, and CT attenuation values at the 2.5^th–97.5^th percentiles on histogram, and texture parameters (uniformity and entropy) were assessed from CT datasets.

Results

Of 191 tumors, 38 were AISs (20%), 61 were MIAs (32%), and 92 (48%) were invasive adenocarcinomas. Multivariate logistic regression analysis helped identify the 75^th percentile CT attenuation value (P = 0.04) and entropy (P<0.01) as independent predictors for invasive adenocarcinoma, with an area under the receiver operating characteristic curve of 0.780.

Conclusion

Quantitative analysis of preoperative CT imaging metrics can help distinguish invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma.

Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas

PURPOSE

To retrospectively investigate the value of computerized three-dimensional texture analysis for differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas (IPAs) that manifest as part-solid ground-glass nodules (GGNs).

MATERIALS AND METHODS

The institutional review board approved this retrospective study with a waiver of patients' informed consent. The study consisted of 86 patients with 86 pathologic analysis-confirmed part-solid GGNs (mean size, 16 mm ± 5.4 [standard deviation]) who had undergone computed tomographic (CT) imaging between January 2005 and October 2011. Each part-solid GGN was manually segmented and its computerized texture features were quantitatively extracted by using an in-house software program. Multivariate logistic regression analysis was performed to investigate the differentiating factors of preinvasive lesions from IPAs. Three-layered artificial neural networks (ANNs) with a back-propagation algorithm and receiver operating characteristic curve analysis were used to build a discriminating model with texture features and to evaluate its discriminating performance.

RESULTS

Pathologic analysis confirmed 58 IPAs (seven minimally invasive adenocarcinomas and 51 invasive adenocarcinomas) and 28 preinvasive lesions (four atypical adenomatous hyperplasias and 24 adenocarcinomas in situ). IPAs and preinvasive lesions exhibited significant differences in various histograms and volumetric parameters (P < .05). Multivariate analysis revealed that smaller mass (adjusted odds ratio, 0.092) and higher kurtosis (adjusted odds ratio, 3.319) are significant differentiators of preinvasive lesions from IPAs (P < .05). With mean attenuation, standard deviation of attenuation, mass, kurtosis, and entropy, the ANNs model showed excellent accuracy in differentiation of preinvasive lesions from IPAs (area under the curve, 0.981).

CONCLUSION

In part-solid GGNs, higher kurtosis and smaller mass are significant differentiators of preinvasive lesions from IPAs, and preinvasive lesions can be accurately differentiated from IPAs by using computerized texture analysis. Online supplemental material is available for this article.

Pure ground-glass opacity neoplastic lung nodules: histopathology, imaging, and management

OBJECTIVE

The purpose of this article is to discuss histologic diagnosis of pure pulmonary ground-glass opacity nodules (GGNs), high-resolution CT (HRCT) findings and pathologic correlation, and management.

CONCLUSION

When pure GGNs are greater than 15 mm in diameter with nodularity or have high pixel attenuation (>-472 HU), the nodules are more likely to be invasive adenocarcinomas. Sublobar resection with a secured safety margin and without nodal dissection is performed for HRCT-suggested pure-GGN invasive adenocarcinomas and has a 100% 5-year survival rate.

Density features of screened lung tumors in low-dose computed tomography

RATIONALE AND OBJECTIVES

Using low-dose computed tomography (LDCT), small and heterogeneous lung tumors are detected in screening. The criteria for assessing detected tumors are crucial for determining follow-up or resection strategies. The purpose of this study was to investigate the capacity of density features in differentiating lung tumors.

MATERIALS AND METHODS

From July 2008 to December 2011, 48 surgically confirmed tumors (29 malignancies, comprising 17 cases of adenocarcinoma and 12 cases of adenocarcinoma in situ [AdIs], and 19 benignancies, comprising 11 cases of atypical adenomatous hyperplasia [AAH] and eight cases of benign non-AAH) in 38 patients were retrospectively evaluated, indicating that the positive predictive value (PPV) of physicians is 60.4% (29/48). Three types of density features, tumor disappearance rate (TDR), mean, and entropy, were obtained from the CT values of detected tumors.

RESULTS

Entropy is capable of differentiating malignancy from benignancy but is limited in differentiating AdIs from benign non-AAH. The combination of entropy and TDR is effective for predicting malignancy with an accuracy of 87.5% (42/48) and a PPV of 89.7% (26/29), improving the PPV of physicians by 29.3%. The combination of entropy and mean adequately clarifies the four pathology groups with an accuracy of 72.9% (35/48). For tumors with a mean below -400 Hounsfield units, the criterion of an entropy larger than 5.4 might be appropriate for diagnosing malignancy. For others, the pathology is either benign non-AAH or adenocarcinoma; adenocarcinoma has a higher entropy than benign non-AAH, with the exception of tuberculoma.

CONCLUSIONS

Combining density features enables differentiating heterogeneous lung tumors in LDCT.

Invasiveness and malignant potential of pulmonary lesions presenting as pure ground-glass opacities

PURPOSE

We retrospectively investigated the pathological diagnoses of pulmonary lesions presenting as pure ground-glass opacities (GGOs) to evaluate the risk of invasive malignancy.

METHODS

We examined 191 GGO lesions, including 114 pure GGO and 77 mixed lesions, in 160 patients who underwent resection between January 2008 and December 2010.

RESULTS

Of the 114 pure GGO lesions, 14 (12%) were diagnosed as invasive lung cancer and 16 (14%) as minimally invasive adenocarcinoma. Twenty-one lesions exhibited pleural indentation on high-resolution computed tomography (HRCT), and 5 of these were diagnosed as invasive cancer, indicating an invasive tendency of pure GGO lesions with pleural indentation (odds ratio, 2.64). Of 14 pure GGO lesions positive on positron emission tomography (PET), 8 were diagnosed as invasive lung cancer, indicating an invasive tendency of pure GGO lesions with PET positivity (odds ratio, 16.0; p <0.001; sensitivity, 67%; specificity, 89%).

CONCLUSION

Invasive lung cancer accounted for 12% of the pure GGO lesions. Pure GGO lesions should be carefully monitored by periodic chest computed tomography, and surgical resection is recommended when they exhibit pleural indentation on HRCT or positivity on PET.

Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study

INTRODUCTION

Pulmonary nodules of the adenocarcinoma spectrum are characterized by distinctive morphological and radiologic features and variable prognosis. Noninvasive high-resolution computed tomography-based risk stratification tools are needed to individualize their management.

METHODS

Radiologic measurements of histopathologic tissue invasion were developed in a training set of 54 pulmonary nodules of the adenocarcinoma spectrum and validated in 86 consecutively resected nodules. Nodules were isolated and characterized by computer-aided analysis, and data were analyzed by Spearman correlation, sensitivity, and specificity and the positive and negative predictive values.

RESULTS

Computer-aided nodule assessment and risk yield (CANARY) can noninvasively characterize pulmonary nodules of the adenocarcinoma spectrum. Unsupervised clustering analysis of high-resolution computed tomography data identified nine unique exemplars representing the basic radiologic building blocks of these lesions. The exemplar distribution within each nodule correlated well with the proportion of histologic tissue invasion, Spearman R = 0.87, p < 0.0001 and 0.89 and p < 0.0001 for the training and the validation set, respectively. Clustering of the exemplars in three-dimensional space corresponding to tissue invasion and lepidic growth was used to develop a CANARY decision algorithm that successfully categorized these pulmonary nodules as "aggressive" (invasive adenocarcinoma) or "indolent" (adenocarcinoma in situ and minimally invasive adenocarcinoma). Sensitivity, specificity, positive predictive value, and negative predictive value of this approach for the detection of aggressive lesions were 95.4, 96.8, 95.4, and 96.8%, respectively, in the training set and 98.7, 63.6, 94.9, and 87.5%, respectively, in the validation set.

CONCLUSION

CANARY represents a promising tool to noninvasively risk stratify pulmonary nodules of the adenocarcinoma spectrum.

IASLC/ATS/ERS International Multidisciplinary Classification of Lung Adenocarcinoma: novel concepts and radiologic implications

In 2011, the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society proposed a new classification for lung adenocarcinoma that included a number of changes to previous classifications. This classification now considers resection specimens, small biopsies, and cytology specimens. Two former histopathologic terms, bronchioloalveolar carcinoma and mixed subtype adenocarcinoma, are no longer to be used. For resection specimens, the new terms of adenocarcinoma in situ and minimally invasive adenocarcinoma are introduced for small adenocarcinomas showing pure lepidic growth and predominantly lepidic growth, with invasion ≤5 mm, respectively. Invasive adenocarcinomas are now classified by their predominant pattern as lepidic, acinar, papillary, and solid; a micropapillary pattern is newly added. This classification also provides guidance for small biopsies and cytology specimens. For adenocarcinomas that include both an invasive and a lepidic component, it is suggested that for T staging the size of the T-factor may be best measured on the basis of the size of the invasive component rather than on the total size of tumors including lepidic components, both on pathologic and computed tomography assessment. This suggestion awaits confirmation in clinical-radiologic trials. An implication for M staging is that comprehensive histologic subtyping along with other histologic and molecular features can be very helpful in determining whether multiple pulmonary nodules are separate primaries or intrapulmonary metastases. In this review article, we provide an illustrated overview of the proposed new classification for lung adenocarcinoma with an emphasis upon what the radiologist needs to know in order to successfully contribute to the multidisciplinary strategic management of patients with this common histologic subtype of lung cancer.

Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

OBJECTIVES

The objective of this article is to update previous evidence-based recommendations for evaluation and management of individuals with solid pulmonary nodules and to generate new recommendations for those with nonsolid nodules.

METHODS

We updated prior literature reviews, synthesized evidence, and formulated recommendations by using the methods described in the "Methodology for Development of Guidelines for Lung Cancer" in the American College of Chest Physicians Lung Cancer Guidelines, 3rd ed.

RESULTS

We formulated recommendations for evaluating solid pulmonary nodules that measure > 8 mm in diameter, solid nodules that measure ≤ 8 mm in diameter, and subsolid nodules. The recommendations stress the value of assessing the probability of malignancy, the utility of imaging tests, the need to weigh the benefits and harms of different management strategies (nonsurgical biopsy, surgical resection, and surveillance with chest CT imaging), and the importance of eliciting patient preferences.

CONCLUSIONS

Individuals with pulmonary nodules should be evaluated and managed by estimating the probability of malignancy, performing imaging tests to better characterize the lesions, evaluating the risks associated with various management alternatives, and eliciting their preferences for management.